
1. 湘潭大学,湖南,湘潭,411105
2. 太原理工大学 煤电清洁智能控制教育部重点实验室,山西,太原,030024
Published:2025
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陈 颉,方贻雪,牛哲文,张巧龙,张晓东,薛屹洵.计及多网耦合时延传播特性的移动储能定价机制研究[J].智慧电力,2025,53(10):115-125.
CHEN Jie, FANG Yixue, NIU Zhewen, et al. Research on Mobile Energy Storage Pricing Mechanism Considering Multi-network Coupling Delay Propagation Characteristics[J]. 2025, 53(10): 115-125.
陈 颉,方贻雪,牛哲文,张巧龙,张晓东,薛屹洵.计及多网耦合时延传播特性的移动储能定价机制研究[J].智慧电力,2025,53(10):115-125. DOI: 10.20204/j.sp.2025.10015.
CHEN Jie, FANG Yixue, NIU Zhewen, et al. Research on Mobile Energy Storage Pricing Mechanism Considering Multi-network Coupling Delay Propagation Characteristics[J]. 2025, 53(10): 115-125. DOI: 10.20204/j.sp.2025.10015.
研究电力-交通网络耦合场景下移动储能(MES)的定价机制,对实现综合能源系统中储能侧灵活调节具有重要意义。首先,提出扩展对数随机用户均衡(ELSUE)模型,以优化多网耦合下的时延传播成本,从而使MES能够快速响应节点电价变化;其次,以独立系统运营商(ISO)作为主博弈者,以最小化日前系统运营成本为目标,MES所有者作为从博弈者,以套利收益最大化为优化目标,构建了一种具有时延补偿能力的MES分层博弈定价模型,并通过双向迭代优化实现节点边际电价与时延成本的动态更新。算例分析表明,与现有定价机制相比,所提定价机制通过抑制时延传播特性对调度决策的负面影响,有效提升了MES所有者的收益,并降低了系统总能源成本。
The study of pricing mechanisms for mobile energy storage (MES) in coupled power-transportation network scenarios is of great significance for achieving flexible regulation on the energy storage side in integrated energy systems. First, an extended logit stochastic user equilibrium (ELSUE) model is proposed to optimize the delay propagation cost in a multi-network coupled environment, enabling MES to respond rapidly to changes in nodal electricity prices. Second, with the independent system operator (ISO) as the leader aiming to minimize day-ahead system operating costs, and MES owners as followers seeking to maximize arbitrage profits, a hierarchical game-theoretic pricing model for MES with delay compensation capability is constructed. Dynamic updates of locational marginal prices and delay costs are achieved through bidirectional iterative optimization. Case studies show that, compared to existing pricing mechanisms, the proposed mechanism effectively enhances the profits of MES owners and reduces the total system energy cost by mitigating the negative impact of delay propagation characteristics on scheduling decisions.
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